The long term goal of this research project is to understand the mechanistic that underlie of speech sounds by cochlear implant (CI) users and, in so doing, gain an understanding of the individual differences in psychophysical characteristics which may explain individual differences in speech perception with a CI. Insights gained from this research will advance our basic knowledge about speech perception and adaptation to major change in the peripheral frequency map. The specific aim of Project I is to predict phoneme identification of individual cochlear implant users, based on their discrimination along specified perceptual dimensions. To achieve this aim we proposed to develop Multi-dimensional Phoneme Identification (MPI) models of speech perception by multi-channel CI users. These psychophysically- based models of explanatory: they do not simply attempt to predict speech perception based on performance in psychophysical tests, they also provide strict and verifiable hypotheses about how CI users encode and process the input auditory signal to identify different speech sounds. The MPI mode has already provided insight into possible psychophysical accounts of a variety of experimental findings in speech perception. Project II addresses the adaptation show by CI users to the percepts elicited by electrical stimulation, which are of higher pitch than the percepts elicited by acoustic stimulation, due to the more- basal-than-normal location of the stimulating electrodes. We propose to measure the time course, the extent, and the possible limitations of the adaptation shown by CI users in response to this more-basal-than-normal stimulation. This goal is important not only because it will provide clinically and scientifically useful insights about speech perception with a CI, but also because the CI population presents a unique opportunity to investigate human adaptation to a modified frequency map, and may therefore allow us to obtain new knowledge about plasticity of the central auditory system in adults. Using the MPI models developed in Project I, we will be able to obtain quantitative estimates of a CI users' adaptation to more-basal-than-normal stimulation.[unreadable]